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024 7 $a10.1007/978-3-642-35060-3
035   $a(CKB)2670000000328017
035   $a(EBL)1082872
035   $a(OCoLC)826853749
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035   $a(PQKBTitleCode)TC0000878401
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035   $a(DE-He213)978-3-642-35060-3
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100   $a20121107d2013      uy         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aAdvanced statistical methods for astrophysical probes of cosmology $edoctoral thesis accepted by the Astrophysics Group of Imperial College London /$fMarisa Cristina March
205   $a1st ed. 2013.
210   $aNew York $cSpringer$d2013
215   $a1 online resource (191 p.)
225 1 $aSpringer theses : recognizing outstanding Ph.D. research,$x2190-5053
300   $aDescription based upon print version of record.
311   $a3-642-44454-7 
311   $a3-642-35059-3 
320   $aIncludes bibliographical references and index.
327   $aIntroduction -- Cosmology background -- Dark energy and apparent late time acceleration -- Supernovae Ia -- Statistical techniques -- Bayesian Doubt: Should we doubt the Cosmological Constant? -- Bayesian parameter inference for SNeIa data -- Robustness to Systematic Error for Future Dark Energy Probes -- Summary and Conclusions -- Index.
330   $aThis thesis explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations. Bayesian model selection provides a measure of how good models in a set are relative to each other - but what if the best model is missing and not included in the set? Bayesian Doubt is an approach which addresses this problem and seeks to deliver an absolute rather than a relative measure of how good a model is.   Supernovae type Ia were the first astrophysical observations to indicate the late time acceleration of the Universe - this work presents a detailed Bayesian Hierarchical Model to infer the cosmological parameters (in particular dark energy) from observations of these supernovae type Ia.
410  0$aSpringer theses.
606   $aAstrophysics
606   $aCosmology
615  0$aAstrophysics.
615  0$aCosmology.
676   $a523.101
700   $aMarch$b Marisa Cristina$0858466
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910437975503321
996   $aAdvanced Statistical Methods for Astrophysical Probes of Cosmology$91916495
997   $aUNINA